AMIS Dataset: Adaptive Multi-Interval Scale for Aggregated Data Normalization

Dataset Description
This dataset accompanies the research article "Adaptive Multi-Interval Scale (AMIS): Optimization of Normalization and Comparison of Aggregated Data" by Gennadiy G. Kravtsov. The dataset contains aggregated and heterogeneous data from various subject domains, processed using the AMIS method.

Author Information
- Author: Gennadiy G. Kravtsov
- Position: Director, Research Center "Applied Statistics"
- Email: 62abc@mail.ru
- ORCID: https://orcid.org/0009-0000-3405-1461

Data Structure

Original Aggregated Data:
1. EGE-history-karelia-2025.xlsx - Aggregated Unified State Exam (EGE) results in History for 2025 (Karelia)
   Source: https://ege.karelia.ru/Default.aspx?pageid=47359
   Format: Frequency distribution of scores

2. Student_Grades_History_Grade11_Raw_Data.xlsx - Distribution of average grades from history teachers for 11th grade
   Source: https://doi.org/10.5281/zenodo.17314061

3. World_Bank_Nominal_GDP_All_Countries_2024.xlsx - GDP data for countries for 2024
   Source: https://data.worldbank.org/indicator/NY.GDP.MKTP.CD

------------------------
Raw Data File Structure:

Column A: Identifier or name (e.g., student code, country name)
Column B: Numerical value for normalization
Row 1: Column headers

Example:
Kod	Avg-Mark_Hist_11
1	3.86
2	3.79
3	4.5

Aggregated Data File Structure:

Column A: Unique value from the measurement scale
Column B: Frequency (number of observations for this value)
Row 1: Column headers

Example:
Scores	Number of Students
8	1
12	1
16	2

Important Requirements:
- File format: Microsoft Excel (.xlsx)
- First row must contain column headers
- No empty cells in data columns
- Only numerical values in the second column
------------------------

AMIS-Normalized Data:
4. EGE-history-karelia-2025_converted_1_AMIS.xlsx - Aggregated EGE data transformed using AMIS method
5. Student_Grades_History_Grade11_Raw_Data_converted_1_AMIS.xlsx - Educational grades transformed using AMIS method
6. World_Bank_Nominal_GDP_All_Countries_2024_converted_2_AMIS.xlsx - GDP data converted using the AMIS method

Heterogeneous Data Correspondence Tables:
7. AMIS_17_table_EGE-history-karelia-2025_Student_Grades_History_Grade11_Raw_Data.xlsx
   - Correspondence between EGE data and educational grades

8. AMIS_17_table_Student_Grades_History_Grade11_Raw_Data_World_Bank_Nominal_GDP_All_Countries_2024.xlsx
   - Interdisciplinary correspondence of heterogeneous data: educational grades and macroeconomic indicators

Software:
9. ANIS_KOD_v1.zip - Python source code for processing aggregated data and a program for converting aggregated and heterogeneous data
   The following libraries and their versions are required for the code to work:
   - pandas - for working with data in DataFrame format
   - numpy - for numerical operations
   - scipy - for interpolation (interp1d)
   - matplotlib - for plotting graphs

Methodological Features of AMIS
- Adaptive normalization of aggregated data based on distribution
- Precision levels: 3, 5, 9, 17 control points
- Inverse transformation for establishing correspondences between heterogeneous scales
- Specialized processing of aggregated data without access to primary data

Application Areas
- Educational analytics: Normalization of aggregated assessment results
- Interdisciplinary research: Comparison of heterogeneous indicators
- Statistical processing of aggregated data
- Visualization and comparison of heterogeneous metrics in unified space

Usage Notes
- All Excel files contain aggregated data and their normalized representations
- Windows OS required for program operation
- Source code provided for reproducibility of aggregated data processing

Citation
When using this data, please cite the accompanying research article and this dataset.

License
CC BY 4.0

Contact
For questions: 62abc@mail.ru
